More than 11 million people are diagnosed with cancer each year; it is estimated that there will be 16 million new cases every year by 2020 (Cho, WSC., Mol Cancer 2007; 6:25). Traditionally, pathologists have played a major role in the initial diagnosis of cancer, and in the morphologic classification and evaluation of the responsiveness of the patient to therapy, based upon analysis of tissue samples (i.e., serial biopsies).
More recently, there has been a significant advancement of our understanding of the molecular origins of different types of cancer and characteristics of tumor aggressiveness, based upon a major expansion of genomic and proteomic data. Cancer cells display a broad spectrum of genetic alterations that include gene rearrangements, point mutations and gene amplifications, which lead to disturbances in molecular pathways regulating cell growth, survival and metastasis. When such changes manifest themselves in patients (from a small percentage to a majority of patients) having a cancerous tumor, or receiving treatment with a chemotherapeutic agent having a particular mechanism of action, discovery and quantification of these changes can be used to identify biomarkers for detecting and developing targeted therapies, and for predicting the clinical response to chemotherapeutic drugs used to treat the disease. The identification of new predictive biomarkers can provide invaluable assistance to clinicians in minimally-invasively and rapidly predicting a patient's response to therapy, selecting the best treatment modality, monitoring response to treatment over the course of therapy, as well as post-therapy, to thereby improve the likelihood of overall and recurrence-free survival. The advantages of the above cannot be understated.
Recent technologies have allowed the detection and isolation of circulating tumor cells (CTCs). CTCs are rare cells present in the blood in numbers as low as one CTC per 106-107 leucocytes. Historically, the detection and capture of such cells has been challenging (Gupta, et al., Biomicrofluidics 6, 024133 (2012)). Techniques currently used for CTC capture include immunomagnetic separation (Cohen, S. J., et al., J. Clin. Oncol. 26, 3213 (2008); Maheswaran, S., et al., N. Engl. J. Med. 359, 366 (2008), membrane filters (Desitter, I., et al., Anticancer Res. 31, 427 (2011), micro-electro-mechanical system chips (Nagrath, S., et al., Nature 450, 1235 (2007)), and dielectrophoretic field-flow fractionation (DEP-FFF) technology (Gupta, V., et al, ibid.).
Generally, CTC detection methods are composed of the following two steps: an enrichment (isolation) process and detection (identification) process (cytometric and nucleic acid techniques), which may or may not be separate from enrichment. Genetic and molecular characterization of CTCs is typically conducted by fluorescent in situ hybridization (FISH), comparative genomic hybridization (CGH), PCR-based techniques, and biomarker immunofluorescent staining. Normally absent from the peripheral blood of a healthy donor, CTC counts have been described to correlate negatively with progression-free survival and overall survival in patients with metastatic, colorectal, breast, and prostate cancer (Gupta, V., et al., ibid.).
Although numbers of CTCs have previously been correlated with patient survival, CTC isolation from a patient blood sample and subsequent molecular analysis of such cells has not been previously reported for the prediction of responsiveness of a patient to treatment with a particular type of chemotherapeutic agent as provided herein, nor have such analyses been widely used to provide a minimally invasive method to predict, guide and monitor the results of cancer therapy.
In certain cancers such as breast cancer, monitoring a patient's response to treatment is an essential component of therapy, since the degree of response can provide important prognostic information related to disease-free and overall survival. Histopathology provides an accurate assessment of treatment efficacy on the basis of the extent of residual tumor and regressive changes within the tumor tissue. However, only 20% of breast cancer patients achieve a pathologic complete response, a fact that necessitates methods for monitoring therapeutic effectiveness early during therapy (Avril, N. et al., The Journal of Nuclear Medicine, 50 (5) Suppl., May 2009, 55S-63S). Early identification of ineffective therapy may also be useful in patients with metastatic breast and other types of cancer due to the number of palliative treatment options. New methods for predicting therapeutic effectiveness prior to and over the course of therapeutic treatment of various cancers, especially methods that are rapid, minimally invasive and available at an early stage of treatment, can help to individualize and guide treatment, avoid ineffective chemotherapies, provide near real-time analyses, and allow early detection in patients at risk for early relapse.
Thus, there remains a need to provide (among other things) new methods for the early assessment and prediction of the efficacy of cancer treatment regimens, in particular in patients undergoing therapy with a DNA-damaging chemotherapeutic agent.
The present disclosure seeks to address these and other needs in the art.